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Articles by Liling Dai
LAFNet: a lightweight neural network with fuzzy attention mechanism for rail surface defect classification
Abstract Rapid and accurate detection of rail anomaly is crucial for railway transportation safety. Although existing deep learning methods have achieved certain progress, they generally suffer from large model parameter sizes and high computational costs, making it difficult to meet the requirements of real-time performance and resource constraints for on-site deployment. To address these challenges, this study proposes a lightweight neural network model (LAFNet) for rail anomaly classification.
Re-administration of AAV-mediated gene therapy for OTOF -related deafness: a single-arm trial
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Abstract Re-administration of adeno-associated virus (AAV)-mediated gene therapy remains challenging due to neutralizing antibodies (NAbs) induced by the initial dose. We previously conducted a single-arm trial showing that single-dose administration of AAV-hOTOF gene therapy in individuals with OTOF-related deafness is safe and leads to hearing improvements.
By Longlong Zhang, Ziwen Gao, Ping Yang, Daqi Wang, Hongbing Yu, Qi Cao, Luoying Jiang, Xiaoyun Chen, Xin Zhang, Xiaoting Cheng, Liheng Chen, Jiake Zhong, Jun Lv, Wei Wang, Liling Dai, Ziyi Zhou, Yuxin Chen, Biyun Zhu, Shaowei Hu, Honghai Tang, Zheng-Yi Chen, Wuqing Wang, Bing Chen, Huawei Li, Yilai Shu, Xintai Fan, Linjie Shi
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Nature
Verified
Multicentre gene therapy for OTOF -related deafness followed up to 2.5 years
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Abstract Autosomal recessive deafness 9, caused by OTOF gene mutations, is characterized by severe-to-complete congenital deafness1. Although gene therapy has shown benefits in a small number of patients2,3,4,5, its safety and efficacy across broader age ranges and longer follow-up periods, as well as predictors of treatment outcomes, remain unclear.
By Xiaoting Cheng, Jun Lv, Yuxin Chen, Xiaoyun Chen, Rongqun Zhai, Liqin Zhang, Yiling Zhang, Juhong Zhang, Di Deng, Zhicheng Huang, Qi Cao, Xin Zhang, Daqi Wang, Yizhe Wang, Liheng Chen, Sha Yu Verified, Luo Guo, Bowen Zhang, Hui Wang, Yi Zhou, Liling Dai, Wei Wang, Longlong Zhang, Yanbo Yin, Guiqing Cheng, Ziyi Zhou, Wuqing Wang, Bing Chen, Wei Lu, Zhiqiang Gao, Dazhi Shi, Yuanping Xiong, Yu Zhao, Wei Yuan, Qin Wang, Guodong Feng, Huawei Li, Zheng-Yi Chen, Yilai Shu, Luoying Jiang, Hongqun Jiang
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Nature
Verified
Defensive and Ion Conductive Surface Layer Enables High Rate and Durable O3‐type NaNi1/3Fe1/3Mn1/3O2 Sodium‐Ion Battery Cathode
Conflict of Interest The authors declare no conflict of interest. Supporting Information Filename Description smll202305019-sup-0001-SuppMat.pdf531.7 KB Supporting Information References 1, , , , , , , , , , , Adv. Mater. 2020, 32, 2000190. 2, , , , , , , Nat. Energy 2017, 2, 17012. 3, , , , , , J. Energy Chem. 2022, 65, 424. 4, , J. Power Sources 2010, 195, 2419. 5, , , , , , , , , , , Nano Energy 2018, 46, 404. 6, , , , , , , , , Adv. Sci. 2018, 5, 1700786. 7, , , Angew Chem Int Ed Engl 2008, 47, 2930.
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